ChatWise用双层推理框架，让聊天机器人更像专业护工。
ChatWise: A Strategy-Guided Chatbot for Enhancing Cognitive Support in Older Adults
- 采用宏观策略规划与微观对话生成结合的双层框架
- 在真实临床数据上表现接近专业护工，交互模拟中获积极反馈
- 无需大量标注数据，适合认知支持场景
老年人认知健康问题日益严峻。尽管对话干预在改善认知福祉方面展现可行性，但人力照护资源仍严重不足。基于AI的聊天机器人虽具潜力，但现有研究多依赖隐式策略或大量训练标签。为此，我们提出策略引导型聊天机器人ChatWise，采用双层对话推理框架，融合宏观策略规划与微观话语生成，实现针对老年群体的自然、多轮互动。实证结果表明，利用真实临床数据进行离线评估时，ChatWise行为高度贴近专业人类护工；在数字孪生体交互模拟中，用户表现出积极的认知与情绪反应，显著优于遵循隐式生成策略的AI基线模型。
原文摘要 · Abstract (English)
Cognitive health in older adults presents a growing challenge. Although conversational interventions show feasibility in improving cognitive wellness, human caregiver resources remain overloaded. AI-based chatbots have shown promise, yet existing work is often limited to implicit strategies or heavily depends on training and label resources. In response, we propose a strategy-guided AI chatbot named ChatWise that follows a dual-level conversation reasoning framework. It integrates macro-level strategy planning and micro-level utterance generation to enable engaging, multi-turn dialogue tailored to older adults. Empirical results show that ChatWise closely aligns with professional human caregiver behaviors in offline evaluation using real clinic data, and achieves positive user cognitive and emotional responses in interactive simulations with digital twins, which significantly outperforms AI baselines that follow implicit conversation generation.
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